Hinge joint damage identification method of soft yoke mooring system based on multibody dynamic modeling and structural monitoring data

Soft yoke mooring system (SYMs) is a single-point mooring system used in shallow water oil and gas development. In general, SYMs consists of mooring framework support, mooring legs, yoke, and single-point turret and it forms a multibody dynamic system with 13 hinge joint structures such as universal joints and thrust bearings. The hinge joint is one of the key components of SYMs; therefore, it is necessary to accurately evaluate the operating behavior of the hinge joints. In this study, real-time damage identification is conducted based on the multibody dynamic features of the SYMs. First, a long-term monitoring strategy for the prototype application is developed based on the multibody governing equations of the SYMs. The motion behaviors and stress state of the hinge joints and bodies are calculated using prototype monitoring data. A hinge joint damage identification based on the virtual moment is proposed by considering the changes in the friction coefficient in the damage state. The virtual moment method is used to transform the damage identification problem of the SYMs into a problem of seeking the optimal solution to the dynamics identification function. Genetic algorithm (GA) is implemented to seek the optimal solution of the friction coefficient of each hinge joint. A large-scale model testing system of the SYMs is established to perform the damage identification of the bottom hinge joints of the SYMs. The results show that the proposed method can effectively identify the damage degree and position of the hinge joints of the SYMs and provide a real-time warning system for the in-service operation of the SYMs.     

密闭舱室突发污染浓度动态预测与源项辨识

潜艇、载人航天器等密闭微环境随着人员停留时间的延长,其舱室空气污染问题已成为危害工作人员生命安全的主要因素,因此迫切需要开展快速准确的污染浓度预测以及对突发不确定污染源辨识的技术研究,并提高密闭环境主动应对突发污染的能力。对舱室污染浓度进行动态预测和污染源项强度辨识是实现舱室空气质量实时预测的关键。建立了集总污染源概念,提出了联合使用卡尔曼滤波和最小二乘算法的舱室突发污染辨识与浓度预测方法,并与建立的变结构污染浓度模型相结合,同时完成了集总污染源散发强度的动态辨识和污染浓度状态预测。另外,在突发污染源定位方面开展了前期的探讨研究工作,建立了一种新的多维浓度离散随机模型,并提出了基于多假设特征匹配的突发污染源定位方法研究。通过匹配观测数据序列与单参数(源位置)多假设获得的传感器处浓度响应序列特征来实现源项定位及散发时间估计,可初步确定源散发强度。     

深海耐压结构健康监测实时安全评估方法和试验验证

文中提出了一种可直接用于深海耐压结构健康监测系统的结构强度安全性评估算法,该算法基于实时监测数据、结构基准状态和系统测量误差,与常规方法相比不需要建立监测对象结构模型.研究出的结构安全性实时评估方法在耐压结构模型压力筒破坏试验中进行了验证,结果表明,结构健康监测系统在耐压结构破坏前发出了报警信息,与常规基于模型的结构安全性评估方法相比,报警压力值提高了0.76 MPa,对深海耐压结构的使用具有重要的工程价值.     

Damage detection of offshore jacket structures using frequency domain selective measurements

The development of damage detection techniques for offshore jacket structures is vital to prevent catastrophic events. This paper applies a frequency response based method for the purpose of structural health monitoring. In efforts to fulfill this task, concept of the minimum rank perturbation theory has been utilized. The present article introduces a promising methodology to select frequency points effectively. To achieve this goal, modal strain energy ratio of each member was evaluated at different natural frequencies of structure in order to identify the sensitive frequency domain for damage detection. The proposed methodology opens up the possibility of much greater detection efficiency. In addition, the performance of the proposed method was evaluated in relation to multiple damages. The aforementioned points are illustrated using the numerical study of a two dimensional jacket platform, and the results proved to be satisfactory utilizing the proposed methodology.     

Detection of nonlinearity effects in structural integrity monitoring methods for offshore jacket-type structures based on principal component analysis

The detection of changes in the dynamic behavior of structures is an important issue in structural safety assessment. The development of detection methods assumes greater significance in the case of offshore platforms because the inherent problems are compounded by the harsh environment. Here, we describe an instrumented physical model for the structural health monitoring of an offshore jacket-type structure and the results of tests in several different damage scenarios. In a comparative investigation of two different methods, we discuss the difficulties of implementing damage detection techniques for complex structures, such as offshore platforms. The combined algorithm of a fuzzy logic system and a model updating method are briefly discussed, and a method based on stochastic autoregressive moving average with exogenous input is adopted for the structure. The consideration of uncertainties and the effects of nonlinearity were major objectives. So, the methods were also investigated based on the test scenarios consisting of the physical model with a geometric nonlinearity. The principal component analysis method was utilized for the detection of nonlinearity in the recorded data. The results show that the developed methods are suitable for damage classification, but the quality of the acquired signals must be considered an important factor influencing successful classification. The development of these methods may be extremely useful, as such technologies could be applied for offshore platforms in service, enabling damage detection with fewer false alarms.     

基于光纤光栅传感技术的圆沉箱靠船墩结构健康监测*

采用FBG传感技术对某港区30万吨级原油泊位工程主体结构圆式沉箱靠船墩进行应变测试;利用虚拟仪器开发软件LabView作为开发平台,建立结构实时健康监测系统.对码头主体工程结构的应力情况进行实时监测、及时识别结构的累积损伤并评估其使用性能,对可能出现的灾害提前预警并建立相应的安全预警机制,提高码头主体工程结构的安全性和可靠性.所监测得出的钢筋应变结果,可以加深对圆沉箱结构在复杂外部环境下动力响应的了解,对类似结构的进一步研究发展具有现实的意义.     

基于虚拟流水的多重约束环境下船体分段车间动态调度

提出了固定位置分段生产和流水式的作业模式结合的分段虚拟流水式建造模式,分析了分段作业-人员-工具-物料-场地多关联约束下的资源调配机制。考虑时间-空间-资源等多重约束,给出了一种基于虚拟流水线生产模式的人员调度算法和场地调度算法,同时以某船厂的实际场地布局和生产建造数据为案例进行了分析讨论。结果表明,提出的算法能够较好的适应分段调度过程的多重约束、动态调整等特点,较大幅度提高分段建造资源的利用效率。     

Detecting damage to offshore platform structures using the time-domain data

A new method that uses time-domain response data under random loading is proposed for detecting damage to the structural elements of offshore platforms. In our study, a time series model with a fitting order was first constructed using the time-domain of noise data. A sensitivity matrix consisting of the first differential of the autoregressive coefficients of the time series models with respect to the stiffness of structural elements was then obtained based on time-domain response data. Locations and severity of damage may then be estimated by solving the damage vector whose components express the degrees of damage to the structural elements. A unique aspect of this detection method is that it requires acceleration history data from only one or a few sensors. This makes it feasible for a limited array of sensors to obtain sufficient data. The efficiency and reliability of the proposed method was demonstrated by applying it to a simplified offshore platform with damage to one element. Numerical simulations show that the use of a few sensors＇ acceleration history data, when compared with recorded levels of noise, is capable of detecting damage efficiently. An increase in the number of sensors helps improve the diagnosis success rate.     

基于模糊神经网络的水下机器人实时状态监测模型

本文提出了基于人工智能的自主式水下机器人推进器及舵状态监测模块结构,基于模糊神经网络技术,以模糊自适应学习控制网络为核心构筑了状态监测模型,提出了基于最大权值矩阵的规则提取及基于浮点数编码的遗传算法参数调整方法,分析了推进器及舵的状态监测过程,并基于监测模型探讨了推进器及舵工作状态的评价方法.通过计算机仿真试验,验证了本文所提方法的有效性和监测模型的可行性.     

港工结构破损状态的预测和评估

本文应用灰色系统理论,提出了预测港工结构破损状态的建模方法和步骤,并给出了用于预测的动态模型,运用这个模型可以预测结构未来时刻所处的状态;建议了不同损伤类型的结构破损状态评定标准,为工程单位决策的科学化提供了参考依据。     

基于GDI+的船用虚拟仪表均匀刻度线的绘制

鉴于船用虚拟仪表在轮机模拟器及船舶机电设备综合监控系统中的重要性,针对传统方法对虚拟仪表刻度线开发的不足,本文基于平面内点关于直线对称的理论提出了一种关于虚拟仪表均匀刻度线新的绘制方法,给出了该方法的详细设计方案以及严密的数学推理,并以VS.net为开发环境结合GDI+技术,采用此方法编写了虚拟船用电流表,以证明该方法的可行性。结果证明,该方法正确有效,能克服传统方法的不足之处,同时还能减少开发人员的工作量,对其他仿真系统仪表控件的开发有良好的借鉴作用。     

多无人水下航行器协同导航与定位研究

提出一种基于移动长基线的多无人水下航行器协同导航与定位方法.多无人水下航行器协同导航与定位方法对于解决大水深和远航程问题至关重要,在移动长基线算法中,主UUV装备高精度导航设备作为移动长基线节点,而从UUv装备低精度导航设备,两者之间通过水声装置米相互定位,利用传统几何关系解算从UUV,位置的算法将产生很大误差.基于扩展卡尔曼滤波的移动长基线算法能有效融合内部和外部传感器信息,提高导航精度.仿真试验对此进行了验证.     

虚拟机舱管路布局算法优化设计

针对当前船舶管路布局设计主要依靠经验丰富的设计人员手动敷设完成,为提高管路自动化布局效率,提出了一种基于改进遗传算法的三维空间管路设计方法,以辅助设计者完成管路布局工作。通过在经典遗传算法的整体框架中引入免疫选择机制,增加免疫检测算子和免疫平衡算子,改进了遗传算法仅依靠适应度值选择后代个体易造成算法陷入局部最优解的不足,维护了种群多样性,提高了算法运行效率。以船舶机舱为对象建立虚拟机舱仿真环境,采用栅格法对布局空间进行划分,以十进制浮点数编码方式进行算法编码设计。MATLAB仿真结果验证了改进遗传算法在管路布局优化设计问题上的可行性和搜索效率,采用C#语言编写脚本控制程序,在Unity3D虚拟机舱环境中实现了管路路径的布局设计。     

基于量子天牛群算法的高桩码头横向排架结构损伤识别

针对高桩码头损伤识别问题,引入量子行为优化天牛群(BSO)算法,利用结构模态参数(固有频率和振型)的差别构造目标函数,提出了一种基于量子天牛群(QBSO)算法的损伤识别方法。采用所提方法对一高桩码头模型单直桩、单叉桩的单损伤,双直桩、双叉桩、直桩+叉桩的双损伤进行了计算,并与天牛群(BSO)算法与粒子群(PSO)算法进行对比;对振型添加噪声后单叉桩的单损伤进行了计算。结果表明:所提方法计算效率高、收敛速度快,具有较强的稳定性和抗噪性,能够快速精准地识别出损伤位置与损伤程度。     

基于EKF的AUV协同定位方法仿真与验证

自主水下航行器（AUV）协同导航定位技术是解决复杂作业环境下导航问题的重要途径,研究了单领航艇的主从式多AUV基于扩展卡尔曼滤波（EKF）算法的协同到导航定位问题。AUV协同定位时,主AUV内部装备高精度导航设备,从AUV内部装备低精度导航设备,外部配有测距装置,舰艇间是通过通信装置来交换自身位置和状态信息并同时测量通信双方的相对距离,通过信息融合对自身定位进行修正,利用EKF算法对系统中传感器所传递信息进行融合,对从AUV进行实时定位。通过仿真验证此算法可以显著提高导航定位精度。     

含损伤加筋板结构声辐射阻尼变异研究

从能量耗散角度提出了结构声辐射阻尼的有关概念,考虑到辐射阻尼的特性,文章采用结构振动时耗散能量与振动总能量的比来建立辐射阻尼的数学模型,并用数值计算的方法研究简支板结构的声辐射阻尼特性.在研究结构损伤对声辐射阻尼影响的时候,以加筋板结构为例,计算结构不同损伤情况下的声辐射阻尼.基于Mindlin理论,建立描述健康和损伤的四结点有限元板壳单元模型,采用有限元方法计算结构表面动力响应.各向同性损伤单元,采取刚度各向整体弱化的方法分析;对于各向异性损伤单元,采用Kachanov理论,引入了x和y两个方向的弹性损伤折减系数.考虑到不同损伤存在形式,计算分析了损伤对声辐射阻尼的影响.文章建立了一种含损结构的分析方法,通过对一些典型算例分析,在评价损伤对船舶与海洋结构物常用的加筋结构声辐射特性影响方面做出了一定的探索.     

一种基于改进的减缩模型修正方法

提出一种改进的模型修正方法,该方法采用多目标优化技术使得结构的减缩模型与实测结果相吻合。即首先建立一个多目标优化模型,其中包括一个关于单元修正系数的隐式非线性特征方程组,然后通过遗传算法来求解该多目标优化问题,来同时实现模型修正和损伤检测。文中通过对一个悬臂梁的数值仿真,表明本文所提出的方法的有效性,即在较大的测量噪声的情况下,同时具有模型修正和损伤检测两种功能,且较改进前的基于迭代的方法具有更好的噪声鲁棒性。     

时间反演在浅海波导环境中的应用研究

本文基于伪谱方法对浅海波导环境中的时间反演聚焦和时间反演主动声纳进行了计算，给出了声源频率为100Hz的正演和反演声场分布的演化过程。     

一种基于增量定位的移动信标辅助节点定位算法

针对网络中可能有少量节点难以接收足够定位信息的情况,提出一种基于增量定位的移动信标辅助节点定位算法。该算法初步考虑节点之间的协作,选取部分节点对接收信息进行转发。仿真结果表明,在移动信标的路径长度和通信半径不变的情况下,该方法可获取较高的定位覆盖率,适用于信标路径间距较大的场合。     

Underwater simultaneous localization and mapping based on forward-looking sonar

A method of underwater simultaneous localization and mapping (SLAM) based on forward-looking sonar was proposed in this paper. Positions of objects were obtained by the forward-looking sonar, and an improved association method based on an ant colony algorithm was introduced to estimate the positions.In order to improve the precision of the positions, the extended Kalman filter (EKF) was adopted. The presented algorithm was tested in a tank, and the maximum estimation error of SLAM gained was 0.25 m. The tests verify that this method can maintain better association efficiency and reduce navigation error.